Quite a few problems crop up here. The most hurtful is that the context of the chart is left to the text. If you read the paragraph above, you'll learn that the data represents only a select group of institutions known as the Russell Group; and in particular, Cambridge University was omitted because "it did not provide data in 2005". That omission is a curious decision as the designer weighs one missing year against one missing institution (and a mighty important one at that). This issue is easily fixed by a few choice words.

You will also learn from the text that the author's primary message is that among the elite institutions, little if any improvement has been observed in the enrollment of (disadvantaged) students from "low participation areas". This chart draws our attention to the tangle of up and down segments, giving us the impression that the data is too complicated to extract a clear message.

The decision to use 21 colors for 21 schools is baffling as surely no one can make out which line is which school. A good tip-off that you have the wrong chart type is the fact that you need more than say three or four colors.

The order of institutions listed in the legend is approximately reverse of their appearance in the chart. If software can be "intelligent", I'd hope that it could automatically sort the order of legend entries.

If the whitespace were removed (I'm talking about the space between 0% and 2.25% and between 8% and 10%), the lines could be more spread out, and perhaps labels can be placed next to the vertical axes to simplify the presentation. I'd also delete "Univ." with abandon.

The author concludes that nothing has changed among the Russell Group. Here is the untangled version of the same chart. The schools are ordered by their "inclusiveness" from left to right.

This is a case where the "average" obscures a lot of differences between institutions and even within institutions from year to year (witness LSE).

In addition, I see a negative reputation effect, with the proportion of students from low-participation areas decreasing with increasing reputation. I'm basing this on name recognition. Perhaps UK readers can confirm if this is correct. If correct, it's a big miss in terms of interesting features in this dataset.